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This location independence provides better performance and scalability than traditional file system architectures.
Our results demonstrate that the streaming SIMD implementation has better performance and scalability.
Results show that bitonic sort on ePUMA multi-core DSP has much better performance and scalability.
Designers of distributed algorithms typically assume strong memory consistency guarantees, but system implementations provide weaker guarantees for better performance and scalability.
Our results indicate that for better performance and scalability, it is important to have (1) fast cache-to-cache communication, (2) large L2 or shared capacity, (3) fast L2 to core latency, and (4) fair cache resource sharing.
Multi-core mixed-criticality systems are complex solutions that provide benefits regarding lower power consumption, size, weight and cost and better performance and scalability, compared with single-core architectures.
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From the physical point of view, these structures do provide better performance and better scalability.
It is known that a group-based system provides better performance and more scalability to the whole system while it decreases the communication traffic.
Our cluster experiments with Montage and BLAST workflows, using up to 512 cores, show that MemFS has both better performance and better scalability than the state-of-the-art, locality-based file system, AMFS.
Our experiments demonstrate that, although spectral methods eliminate the spatial dispersion errors and can lead to a reduced computational complexity, finite difference migrations are able to achieve the same accuracy with both a better performance and a better scalability in many cases because of the more regular computation and memory access patterns.
Thus, many aspects of DCA systems must be investigated and evaluated to achieve better performance, scalability, and security.
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